A Multi Fuzzy-based Variable Step Size P&O MPPT Algorithm for PV Systems

Photovoltaic (PV) system transforms sunlight into electricity. PV cells have non-linear I-V relationships with one point producing the maximum power output from the PV cells. The best efficiency is obtained at the maximum power point (MPP) of PV system. This paper proposes a hybrid MPP control strategy that incorporates both fuzzy logic controller (FLC) and the Perturbation and Observation (P&O) algorithm under various cases of whether conditions. The proposed algorithm is continuously searching for maximum power point and modify it as needed under rapidly changing weather conditions (irradiance and temperature) and be able to perform successful tracking of the MPP under partially shaded conditions. The performance and the power output of the system will be evaluated using simulation under specific weather conditions. The developed controller is implemented in two stages to overcome the drawbacks of the conventional P&O algorithm; the first stage uses fuzzy controller to provide an initial guess for P&O where it combines the speed of FLC approximation with the accuracy of P&O. The second stage uses another fuzzy controller to find a proper step size of P&O to enhance the transient response and reduce the steady-state oscillations. The results show that the efficiency of the proposed remains high under various scenarios; Uniform irradiation, sudden irradiation, partial shading (weak, moderate, and strong). Furthermore, results demonstrated that the proposed hybrid FLC-P&O can effectively improve the accuracy of the conventional P&O algorithm.